| Literature DB >> 27778208 |
David James Davies1,2, Michael Clancy3, Daniel Lighter4, George M Balanos5, Samuel John Edwin Lucas5, Hamid Dehghani3, Zhangjie Su6,7, Mario Forcione8, Antonio Belli6,8,7.
Abstract
The Near-infrared spectroscopy (NIRS) has not been adopted as a mainstream monitoring modality in acute neurosurgical care due to concerns about its reliability and consistency. However, improvements in NIRS parameter recovery techniques are now available that may improve the quantitative accuracy of NIRS for this clinical context. Therefore, the aim of this study was to compare the abilities of a continuous-wave (CW) NIRS device with a similarly clinically viable NIRS device utilising a frequency-domain (FD) parameter recovery technique in detecting changes in cerebral tissue saturation during stepwise increases of experimentally induced hypoxia. Nine healthy individuals (6M/3F) underwent a dynamic end-tidal forced manipulation of their expiratory gases to induce a stepwise induced hypoxia. The minimum end-tidal oxygen partial pressure (EtO2) achieved was 40 mm Hg. Simultaneous neurological and extra-cranial tissue NIRS reading were obtained during this protocol by both tested devices. Both devices detected significant changes in cerebral tissue saturation during the induction of hypoxia (CW 9.8 ± 2.3 %; FD 7.0 ± 3.4 %; Wilcoxon signed rank test P < 0.01 for both devices). No significant difference was observed between the saturation changes observed by either device (P = 0.625). An observably greater degree of noise was noticed in parameters recovered by the FD device, and both demonstrated equally variable baseline readings (Coefficient of variance 8.4 and 9.7 % for the CW and FD devices, respectively) between individuals tested. No advantageous difference was observed in parameters recovered from the FD device compared with those detected by CW.Entities:
Keywords: Cerebral blood flow; Continuous-wave near-infrared spectroscopy; Frequency-domain near-infrared spectroscopy; Head injury
Mesh:
Substances:
Year: 2016 PMID: 27778208 PMCID: PMC5599440 DOI: 10.1007/s10877-016-9942-5
Source DB: PubMed Journal: J Clin Monit Comput ISSN: 1387-1307 Impact factor: 2.502
Fig. 1Beer–Lambert concept
Fig. 2Suzuki SRS concept illustrated
Fig. 3Frequency-domain concept
Fig. 4NIRS position and DEF illustrated
Fig. 5Isocapnic hypoxia protocol
Table of baseline means and coefficients of variance (CV) Wilcoxon rank test significance
| Baseline TOI (%) (mean ± CV) | Hypoxia TOI (%) (mean ± CV) | Post release TOI (%) (mean ± CV) | |
|---|---|---|---|
| NIRO Forehead | 63.2 ± 8.4 | 53.4 ± 11.9 | 62.7 ± 11.1 |
| NIRO Zygoma | 77.0 ± 10 | 68.3 ± 9.54 | 77.9 ± 10.2 |
| ISS Forehead | 61.8 ± 9.7 | 54.8 ± 7.93 | 62.8 ± 9.9 |
| ISS Zygoma | 72.7 ± 6.8 | 64.1 ± 5.26 | 72.4 ± 6.7 |
Fig. 6Typical participant plot, illustrating FD related noise